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Part Time Data Analyst R Programming Jobs (NOW HIRING)

FOOTHILLS ANIMAL SHELTER

Data Analyst

Golden, CO · Hybrid

$30 - $33/hr

This is a part-time, hourly, hybrid position with a minimum of one day onsite per week at our ... Bachelor's degree in data analytics, statistics, business, computer science, or related field. OR

Futran Tech Solutions Pvt. Ltd.

Sr. Data Analyst

$88K - $111K/yr

We are requesting a part-time (50%) Sr Data Analyst contractor from the US, who can be available as early as 730 PT to work with our offshore IST team and support multiple projects. The location ...

Booz Allen Hamilton, Inc.

Cyber Data Analyst

Chantilly, VA · On-site

$62K - $141K/yr

Share Cyber Data Analyst The Opportunity: As a cyber data analyst, you love diving into data and ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

One Call

Data Analyst II

$55K - $83K/yr

... Part-time Full Time Salary Range Min - Max (USD) $55700 - $83500 Country United States Date 30-Jun ... Analyze data and design/generate reports that evaluate program performance for both internal and ...

One Call

Data Analyst II

$55K - $83K/yr

... Part-time Full Time Salary Range Min - Max (USD) $55700 - $83500 Country United States Date 30-Jun ... Analyze data and design/generate reports that evaluate program performance for both internal and ...

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All JobsData Analyst R Programming JobsPart Time Data Analyst R Programming Jobs

Part Time Data Analyst R Programming information

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$34K

$82.6K

$136K

How much do part time data analyst r programming jobs pay per year?

As of Jul 8, 2026, the average yearly pay for part time data analyst r programming in the United States is $82,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,500.00 and $97,000.00 per year, depending on experience, location, and employer.

Is 40 too late for data science?

Age is not a barrier to becoming a data analyst or data scientist; many professionals transition into the field later in life. Success depends on acquiring relevant skills such as R programming, statistical knowledge, and experience with data tools, regardless of age.

What is the difference between Part Time Data Analyst R Programming vs Part Time Data Analyst Python?

AspectPart Time Data Analyst R ProgrammingPart Time Data Analyst Python
Required SkillsProficiency in R, data visualization, statistical analysisProficiency in Python, data manipulation, machine learning
Work EnvironmentData analysis, reporting, statistical modelingData analysis, automation, machine learning projects
Industry UsageResearch, healthcare, financeTech, finance, marketing

Both roles involve data analysis in a part-time setting but differ mainly in programming language expertise. R is favored for statistical analysis and visualization, while Python is preferred for automation and machine learning tasks. Your choice depends on the specific tools and industry focus.

Will AI replace a data analyst?

AI can automate routine data processing and basic analysis tasks, but a data analyst's role involves interpreting complex data, providing insights, and making strategic decisions that require human judgment. Skills in programming, statistical analysis, and understanding business context remain essential for data analysts to add value beyond automation.

Are R programmers in demand?

R programmers, including those with expertise in data analysis and statistical modeling, are in demand across industries such as finance, healthcare, and technology. Skills in R, along with knowledge of data visualization and data manipulation, increase employability in roles like data analyst and data scientist, especially as companies prioritize data-driven decision-making.

Is R important for data analysts?

R is a widely used programming language for data analysts, especially in statistical analysis and data visualization. Proficiency in R can enhance a data analyst's ability to manipulate data, perform complex analyses, and generate reports, making it a valuable skill in the field.
More about Part Time Data Analyst R Programming jobs
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Part Time Data Analyst R Programming jobs near you
Infographic showing various Part Time Data Analyst R Programming job openings in the United States as of July 2026, with employment types broken down into 1% Locum Tenens, 1% Internship, 86% Full Time, 6% Part Time, 1% Temporary, and 5% Contract. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution, with an average salary of $82,640 per year, or $39.7 per hour.
Part- Time Research Data Analyst

Part- Time Research Data Analyst

Penn State University

University Park, PA • On-site

Part-time

Posted 13 days ago

Penn State University rating

7.8

Company rating: 7.8 out of 10

Based on 103 frontline employees who took The Breakroom Quiz

196th of 546 rated colleges and universities

Job description

APPLICATION INSTRUCTIONS:
  • CURRENT PENN STATE EMPLOYEE (faculty, staff, technical service, or student), please login to Workday to complete the internal application process. Please do not apply here, apply internally through Workday.
  • CURRENT PENN STATE STUDENT (not employed previously at the university) and seeking employment with Penn State, please login to Workday to complete the student application process. Please do not apply here, apply internally through Workday.
  • If you are NOT a current employee or student, please click "Apply" and complete the application process for external applicants.

Approval of remote and hybrid work is not guaranteed regardless of work location. For additional information on remote work at Penn State, see Notice to Out of State Applicants.
JOB DESCRIPTION AND POSITION REQUIREMENTS
Program Description
The Research Translation Platform invites applications for a Research Data Analyst interested in a career at the research-policy nexus supporting the evaluation and analytic needs of strategies for translating scientific evidence to policymakers. This exciting opportunity would support the analysis and evaluation of research translation models, such as the Research-to-Policy Collaboration model. The Analyst would be responsible for supporting methods development and data analysis for a variety of projects, and may have opportunities to contribute to the implementation of an effective, replicable and non-partisan model for brokering researchers and policymakers. While the Analyst should have advanced quantitative skills, prior policy experience is not required. Training and mentorship in applying their skills to the analysis of boundary-spanning initiatives will be provided. This mentored position provides an opportunity to learn translational skills while working with policymaking audiences, as well as opportunities to contribute to scholarly work regarding best practices for research translation and dissemination. Our team is hybrid academic and policy practice; thus, we use data for action. Preference will be given to those within commuting distance to the Washington, D.C. area, though it is not required.
Job Responsibilities
  • Design the plan for and analyze observational and survey data regarding policymakers' or researchers' engagement in boundary-spanning initiatives, including longitudinal and multi-level analyses
  • Extract, transform, clean, and maintain data from a variety of sources
  • Development and proactive upkeep of data sources (e.g., surveys in Redcap, observational data via a CRM)
  • Contribute to the development of analytic plans for grants and publications
  • Support analytic needs for grant writing and reporting (e.g., power analyses; interim impact analyses)
  • Meet with legislators or staff to collect survey data
  • Mentor undergraduate- and graduate-level interns and fellows on developing and executing analytic plans
  • Juggle multiple projects and move ideas into action with attention to methodological and analytic details
  • Support research planning by setting milestone goals and incremental internal deadlines to achieve goals

Skills and Traits Needed by Applicants
  • Excellent analytic abilities and advanced quantitative statistical modeling skills (e.g., longitudinal, multi-level, over dispersed) of large, messy datasets
  • Proficient with statistical programming software and languages (e.g., SAS, STATA, or R)
  • Excellent attention to detail
  • Applied research experience, such as large administrative datasets or real-world data
  • Enthusiasm and commitment to accelerating the translation of science to policy
  • Curiosity and a generalist attitude with interest in diverse social policy issues
  • Ability to work on multiple simultaneous projects and prioritize work based on project scope, organizational need, and timeline
  • Strong diplomatic communication and interpersonal skills
  • Strong communication skills, such as seeking input early in design and escalating threats or problems to PIs
  • Ensuring quality control of data collection, and alerting PIs as needed
  • Strong writing skills that can produce written sections of methods and results for peer review publication
  • Bipartisan mindset and ability to interpret findings from multiple viewpoints

Eligibility
  • Master's degree or higher; applicants may have their degrees from any department, but degrees in psychology, public health, human development, public policy, social work, or prevention science will be particularly good fits for the program.
  • While the RTP team primarily operates remotely, preference will be given to applicants in Virginia within commuting distance of Washington, D.C. to support in-person data collection from congressional staff
  • Applicants should review the list of states in which Penn State cannot support employment. Permanent residence must be established in an allowable state prior to position start date. https://hr.psu.edu/more/flexible-work-arrangements/out-of-state-notice
  • Remote work requires high-quality, high speed internet connection in a home office

Application Instructions
Full consideration will be given to those applicants who completely submit all materials online. A complete submission will consist of:
  • Cover Letter describing relevant experience and career goals
  • Resume or CV
  • Writing Sample (preferably samples of work directed toward academic audiences; 1-2 samples, 35-page cumulative max)
  • Three references. We will not contact references without your express permission, which may be requested in later stages of the interview process.

Supervision will be provided by Executive Director, Taylor Scott, Ph.D., and Director of Research and Evaluation, Elizabeth Long, Ph.D. Additional mentorship provided by Max Crowley, Ph.D., Professor at Pennsylvania State University.
BACKGROUND CHECKS/CLEARANCES
Employment with the University will require successful completion of background check(s) in accordance with University policies.
CAMPUS SECURITY CRIME STATISTICS
Pursuant to the Jeanne Clery Disclosure of Campus Security Policy and Campus Crime Statistics Act and the Pennsylvania Act of 1988, Penn State publishes a combined Annual Security and Annual Fire Safety Report (ASR). The ASR includes crime statistics and institutional policies concerning campus security, such as those concerning alcohol and drug use, crime prevention, the reporting of crimes, sexual assault, and other matters. The ASR is available for review here.
EEO IS THE LAW
Penn State is an equal opportunity employer and is committed to providing employment opportunities to all qualified applicants without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. If you are unable to use our online application process due to an impairment or disability, please contact 814-865-1473.
Penn State is committed to and accountable for advancing equity, respect, and belonging. We embrace individual uniqueness, as well as a culture of belonging that supports equity initiatives, leverages the educational and institutional benefits of inclusion in society, and provides opportunities for engagement intended to help all members of the community thrive. We value belonging as a core strength and an essential element of the university's teaching, research, and service mission.
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